From the 1 of 9 linked papers with an AI index.
5 papers · 1 filter
Smooth Neural Point Processes via B-Splines
Michele Bellomo, Riccardo Ramaschi, Alberto Dolara +1
Temporal point processes (TPPs) provide a general and flexible framework for modeling sequences of events in continuous time. Neural networks have been successfully employed to mod…
Graph Regularized PCA
Antonio Briola, Marwin Schmidt, Fabio Caccioli +4
The paper introduces Graph Regularized PCA (GR‑PCA), a PCA variant that learns a sparse precision graph and regularizes loadings toward low‑frequency graph Laplacian modes to prese…
Information Filtering Networks: Theoretical Foundations, Generative Methodologies, and Real-World Applications
Tomaso Aste
Information Filtering Networks (IFNs) provide a powerful framework for modeling complex systems through globally sparse yet locally dense and interpretable structures that capture…
Granger Causality Detection with Kolmogorov-Arnold Networks
Hongyu Lin, Mohan Ren, Paolo Barucca +1
Discovering causal relationships in time series data is central in many scientific areas, ranging from economics to climate science. Granger causality is a powerful tool for causal…
Unraveling the Enigma of Double Descent: An In-depth Analysis through the Lens of Learned Feature Space
Yufei Gu, Xiaoqing Zheng, Tomaso Aste
Double descent presents a counter-intuitive aspect within the machine learning domain, and researchers have observed its manifestation in various models and tasks. While some theor…